Coregistration of Hyperspectral Imagery With Photogrammetry for Shallow-Water Mapping

In this article, we present coregistration of hyperspectral imagery with photogrammetry for shallow-water mapping from an unmanned aerial vehicle (UAV). The coregistration is based on a methodology for georeferencing that utilizes the outputs from the photogrammetry pipeline through three steps. First, we perform the photogrammetry pipeline. This gives camera poses from structure-from-motion (SfM) and a dense point cloud from multiview stereo (MVS). Performing a refraction correction of the dense point cloud yields high-resolution bathymetry. Second, poses from SfM are fused with UAV navigation sensors in a Kalman smoother. Third, the geometric model of the hyperspectral imager (HSI) is calibrated to align hyperspectral images with photogrammetry. Then, ray tracing is performed to georeference spectral measurements onto the bathymetry from MVS. Using the georeferenced hyperspectral imagery, we present spectral bathymetry estimation. The methods were demonstrated for a coastal site (depth < 6 m) in Norway, using a UAV with a camera and an HSI. The georeferencing yielded a horizontal mean absolute error (MAE) of 22 cm between hyperspectral and photogrammetry, equivalent to one hyperspectral pixel. The MVS bathymetry gave an MAE of 14 cm with respect to ground-truth acoustics. The spectral bathymetry estimator was calibrated on ground-truth acoustics with an MAE of 10 cm. Comparing the bathymetry from MVS with the spectral bathymetry yielded an MAE of 11 cm. The results suggest that coregistration with photogrammetry yields accurate georeferencing of hyperspectral imagery. The results also show that we can map bathymetry accurately using MVS with refraction correction or the spectral estimator.